DevOps Engineer - AWS, Kubernetes & CI/CD Expert

MACHINE LEARNING TECHNOLOGIES LLC; Columbia (SC); On-site; USD 82,000 - 117,000; Full time

Job summary

Machine Learning Technologies LLC is seeking a seasoned DevOps Engineer to manage cloud infrastructure, automate deployments, and improve application delivery. The ideal candidate will bring hands-on experience with AWS, CI/CD, Docker, Kubernetes, and Terraform, collaborating with development and operations teams to ensure reliable, scalable services.

The role emphasizes building robust pipelines, provisioning infrastructure, and monitoring performance to quickly address production issues while

Qualifications

• 5+ years of DevOps experience.
• Strong knowledge of AWS, Linux, and cloud infrastructure.
• Hands-on experience with Docker and Kubernetes.
• Experience with Jenkins and CI/CD automation.
• Proficiency in Terraform, Ansible, and Python or Shell scripting.
• Knowledge of Git, monitoring, and deployment tools.

Responsibilities

• Design and maintain cloud infrastructure using AWS.
• Develop and manage CI/CD pipelines using Jenkins, GitHub Actions, or GitLab.
• Automate infrastructure provisioning using Terraform and Ansible.
• Build and deploy applications using Docker and Kubernetes.
• Monitor application performance and troubleshoot production issues.
• Work closely with development and operations teams.

Skills

DevOps experience

CI/CD discipline

Communication

Tools

AWS

Linux

Docker

Kubernetes

Jenkins

Git

Terraform

Ansible

Python/Shell scripting

Prometheus/Grafana

Helm

Job description

Machine Learning Technologies LLC is seeking a seasoned DevOps Engineer to manage cloud infrastructure, automate deployments, and improve application delivery. The ideal candidate will bring hands-on experience with AWS, CI/CD, Docker, Kubernetes, and Terraform, collaborating with development and operations teams to ensure reliable, scalable services.

The role emphasizes building robust pipelines, provisioning infrastructure, and monitoring performance to quickly address production issues while